State-Level Energy Efficiency Potential in the U.S. Single-Family Housing Stock

October 29, 2017
Winter 2017
A version of this article appears in the Winter 2017 issue of Home Energy Magazine.
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A homeowner needs to replace an HVAC system. What replacement equipment best meets the multiple goals of affordability, energy efficiency, and comfort? Is the upfront cost of a highly efficient variable-speed heat pump in the homeowner’s best interest? Or is the homeowner better off installing a more efficient version of the current equipment?

Energy efficiency programs may be given an energy savings goal to meet. What are the most cost-effective ways to achieve those savings?

Home performance contractors are called upon to answer questions like these. There is now a tool that can answer these questions at various scales—national, state, and local (see “Example Applications”). ResStock, a residential building stock model, is a newly available public domain tool created at the National Renewable Energy Laboratory (NREL) to inform residential energy efficiency upgrades and program design. ResStock can assess the technical and economic potential of upgrades across fuel types—electricity, natural gas, propane, and fuel oil. Various cost-effectiveness thresholds can be used to evaluate economic potential in ResStock. Examples include net present value, simple payback period, savings-to-investment ratio, and utility program cost-benefit tests.

Example Applications

ResStock analysis can be used to answer questions for a variety of applications:

Home Performance Contractors and Manufacturers

What replacement equipment best meets our three goals
of affordability, energy efficiency, and comfort?

How does market size for our technology vary regionally?

States and Local Communities

What key upgrades by house type are prevalent in our state
or city?

How can we optimize incentive programs to make upgrades more appealing to residents?

How large a role can buildings play in meeting our state’s or city’s energy or emissions goals?

Utilities

Which targeted energy efficiency improvements based on each segment of housing stock pass cost-effectiveness tests?

Which energy efficiency measures and distributed energy
resources are best for relieving grid congestion? Which ones are best for facilitating more variable energy resources on the grid?

Development of ResStock began in 2013 for DOE and has benefited from partnerships with the Bonneville Power Administration; U.S. Environmental Protection Agency; Tendril; the City of Boulder, Colorado; and Radiant Labs. Currently, ResStock can assess the energy efficiency potential of single-family detached homes, but work is under way to expand that capability to include single-family attached homes and low-rise multifamily buildings.

Although ResStock is a relatively new tool, it has already been used for a number of analyses with real-world implications. ResStock was used to evaluate cost-effective energy efficiency potential in the U.S. single-family housing stock for DOE’s Office of Energy Policy and Systems Analysis. This analysis informed DOE’s Quadrennial Energy Review Second Installment: Transforming the Nation’s Electricity System (2017) and resulted in a comprehensive set of maps, tables, and figures showing the technical and economic potential of 50+ residential energy efficiency upgrades and packages for the 48 contiguous states, with the potential to save consumers $49 billion annually.

The Home Improvement Catalyst (HI-Cat) is a new initiative by the DOE Building Technologies Office. It focuses on high-impact opportunities to achieve energy savings in home improvements already planned by homeowners. The designers of this initiative used ResStock to evaluate the cost-effective savings potential of home improvement packages centered on various building trades.

Ways to Benefit

ResStock is open source and free to use for your own analysis.

There are several ways to take advantage of ResStock’s capabilities.

  • NREL technical report. Use ResStock to gain insights from the national- and state-level results found in the NREL technical report Electric End-Use Energy Efficiency Potential in the U.S. Single-Family Housing Stock (Wilson et al., 2017). Selected results from this report are presented in this article.
  • State fact sheets. State audiences can benefit from the series of fact sheets developed for each of the 48 contiguous U.S. states. Each fact sheet presents the potential for economic energy and utility bill savings for the state. The top ten energy saving home improvements are highlighted.
  • Interactive web visualizations. Explore existing analysis results on ResStock’s interactive website. State-level results can be filtered to identify the savings potential in various segments of the housing stock, whether that is homes of a certain vintage, homes with a certain type of heating fuel, or homes with a certain type of wall construction.
  • Analyze your scenario. Use the free and open-source software yourself, or partner with NREL or a third-party consultant. Analyze the scenarios of interest to you, whether you wish to evaluate the potential of a specific technology, define your own cost-effectiveness equations, or plug in hyperlocal data to get a high-granularity picture of the potential in a city or utility service territory. Analysis results can be privately uploaded to the ResStock website for quick visualization.

Unique Capabilities of ResStock

Typical approaches for assessing energy efficiency potential use deemed savings or a limited number of modeled buildings. This low resolution can significantly underestimate or overestimate the economic potential of energy efficiency technologies when pass-fail cost-effectiveness tests are applied.

ResStock is unique in the high level of granularity—and therefore accuracy—used to model the diversity of housing stock characteristics and climates. Figure 1 demonstrates how cost-effective energy efficiency upgrades can be missed if the typical low-resolution approach is used.

To represent the entire U.S. single-family detached housing stock of approximately 80 million homes, ResStock uses 350,000 representative home types distinguished by characteristics such as those used in the high-granularity approach (Figure 1).

Payback Periods

Payback Periods
Figure 1. The colored rectangles represent the payback period of drill-and-fill wall cavity insulation in various segments of the housing stock in a region, divided by 16 weather locations. In this example, only electrically heated single-family homes in the region that have empty wall cavities are represented (about 500,000 homes). In the typical approach, left, payback is evaluated for “average” homes in each weather location, and the measure has a simple payback period of less than five years (SPP < 5) in about 90,000 homes, represented by the green rectangles. In the high-granularity approach used by ResStock, right, additional variables, such as home vintage, size, shape, foundation type, and occupancy, are used to segment the housing stock with finer resolutions. The measure has an SPP < 5 in about 270,000 homes. A significant number of homes where the upgrade has an SPP < 5 years were overlooked with the typical approach, where the high-granularity green and red segments of the housing stock are often hidden within the “average” segments represented by the coarse orange blocks.

ResStock is also well suited to identify opportunities for whole-building retrofits and total energy efficiency saving potential across multiple upgrades. In addition to evaluating individual upgrades, ResStock can combine the 50+ upgrades in packages that account for upgrade interactions. For example, to find packages of the most cost-effective upgrades for each of the 350,000 representative home types, ResStock chose the upgrade with the highest positive net present value in each category for inclusion in the package (Figure 2). This procedure is comparable to how energy auditors or home performance contractors develop recommended packages of upgrades, but was done automatically and on a large scale.

Tailored Upgrade Packages

Tailored Upgrade Packages
Figure 2. This diagram illustrates the automated process used to develop tailored packages of efficiency upgrades for each of the representative 350,000 homes.

Identifying Energy Efficiency Potential Across the United States

The Quadrennial Energy Review analysis identifies priorities for residential energy efficiency initiatives at national, regional, and state levels. Individual upgrades were evaluated using the net present value greater than zero (NPV > 0) and the simple payback period less than five years (SPP < 5) cost-effectiveness threshold.

The upgrade packages constructed with the procedure in Figure 2 save an estimated 4.2 quadrillion Btu per year of primary energy—electricity, natural gas, propane, and fuel oil, which is 24% of consumption by the single-family detached housing stock, and 4.3% of total annual U.S. primary energy consumption (Figures 2 and 3). These are packages with a positive net present value for the homeowner—more than paying for themselves in terms of utility bill savings over their useful life. Similarly, the packages reduce carbon emissions of the stock by 24% (291 million metric tons CO2 per year).

The annual energy savings assumes full turnover of the stock of equipment and appliances, which could take 15–30 years to wear out and be replaced, depending on the type of equipment. Nonequipment upgrades (e.g., insulation and air-sealing upgrades) would also take many years to reach full adoption.

Per-House Aggregate and Average Primary Energy Savings

Per-House Aggregate and Average Primary Energy Savings Figure 3. Per-house primary energy savings are shown for packages of the most cost-effective upgrades in each home across all categories (NPV > 0 economic potential).

Figure 3 shows how the 4.2 quads per year of economic potential (NPV > 0) primary energy savings are distributed across the states (area of bubbles). The bubble colors indicate the average savings per house.

Percentage Savings, Primary Energy Consumption

Percentage Savings, Primary Energy Consumption Figure 4. Percentage savings of each state’s single-family detached primary energy consumption are shown for packages of the most cost-effective upgrades in each home across all categories (NPV > 0 economic potential).

Most states can save 15–30% of single-family home primary energy use cost-effectively (see Figure 3). Alternative packages limited to upgrades within a building trade were also simulated using the NPV > 0 threshold. Often the same contractor will be able to perform all of the enclosure upgrades (Figure 4) or all of the HVAC upgrades (Figure 5), increasing the odds that the homeowner will undertake several upgrades at once.

Enclosure Upgrades Aggregate and Average Primary Energy Savings

Enclosure Upgrades Aggregate and Average Primary Energy Savings
Figure 5. Per-house primary energy savings are shown for packages of enclosure upgrades (NPV > 0 economic potential). Enclosure building trade upgrades include air sealing, attic insulation, wall insulation, foundation insulation, and low-e storm windows. Packages of thermal-enclosure upgrades result in 1,783 Btu per year of economic potential primary energy savings, with greater savings in colder climates. Since enclosure upgrades do not depend on turnover of equipment stock, implementation and accrual of savings can begin immediately.

HVAC Upgrades Aggregate and Average Primary Energy Savings

HVAC Upgrades Aggregate and Average Primary Energy Savings
Figure 6. Per-house primary energy savings are shown for packages of HVAC upgrades (NPV > 0 economic potential.

HVAC building trade upgrades include heating equipment, cooling equipment, duct sealing and insulation, and smart thermostat. Packages of HVAC equipment upgrades result in 1,618 trillion Btu per year of economic potential primary energy savings. These savings are similar in magnitude to the savings potential of enclosure packages, but tend to be greater in southern states, in contrast with the savings potential of enclosure packages, which tends to be greater in northern states.

Top-Priority Upgrades Nationally

Using the NPV > 0 threshold, many of the efficiency upgrades and the packages have economic potential that is at least 90% of technical potential. This suggests that there are a significant number of homes in which the upgrades and packages are attractive investments for economically rational consumers with sufficient upfront cash or financing. Table 1 lists the top 11 national efficiency upgrades contributing to economic potential primary energy savings (using the NPV > 0 filter). The potential for energy savings from some of these measures can vary dramatically across the country, as can be seen in the geographical distribution of savings for drill-and fill wall cavity insulation and upgrading an electric furnace to a high-efficiency heat pump (Figures 6 and 7).

Table 1. Top Efficiency Upgrades Contributing to Economic Potential

Table 1. Top Efficiency Upgrades Contributing to Economic Potential

Savings for Drill-and-Fill Insulation

HVAC Upgrades Aggregate and Average Primary Energy Savings Figure 7. Primary energy savings (NPV > 0 economic potential) are shown for drill-and-fill wall cavity insulation.

Drill-and-fill wall cavity insulation has greater economic potential in states that have older housing stock and colder climates.

Savings from Heat Pump Upgrade

Savings from Heat Pump Upgrade Figure 8. Primary energy savings (NPV > 0 economic potential) are shown for upgrades from an electric furnace to variable-speed heat pump at wear out.

Upgrading electric furnaces (and air conditioners) to variable-speed heat pumps at wear out has greater potential in the Southeast, where more electric furnaces are used for heating.

Market penetration often drops off steeply for payback periods at around five years, so we also evaluated individual upgrades with an economic threshold of SPP < 5. This version of economic potential begins to incorporate consumers’ desire or need for short payback periods. In contrast to the NPV > 0 filter, the SPP < 5 filter removes a large fraction of the potential savings for most of the upgrades. For these upgrades, the longer payback periods are probably a barrier to market adoption.

Five upgrades stand out as retaining 90–100% of technical potential after applying the SPP < 5 years filter:

  • Upgrade electric furnace to variable-speed heat pump at wear out (95%).
  • Upgrade to smart thermostat (occupants not home during the day) (94%).
  • Upgrade to Energy Star clothes washers (99%).
  • Upgrade to Energy Star refrigerators (100%).
  • Replace incandescent with LED lighting in 95% of fixtures (100%).

Producing Actionable Results with ResStock

Low-Income Communities

NREL is working with EPA and DOE to give ResStock the ability to look at results for specific ranges of household income, so that state and federal programs can better understand the opportunities for energy efficiency in low-income and moderate-income communities.

Load Modeling and Time Value of Energy Efficiency

NREL is working with several partners to give ResStock the ability to model subhourly electric demand under different technology scenarios. This work supports a DOE study on the future of the electricity grid, as well as an analysis of the time value of energy efficiency upgrades. NREL is partnering with Tendril—which provides connected home energy management solutions for utility companies—to estimate the potential for peak demand reduction resulting from its software platform in different utility service territories.

City-Scale Analytics for Boulder, Colorado

Software company Radiant Labs has built a suite of analytics tools for the city of Boulder, Colorado, that leverage ResStock analysis capabilities. A targeting and citywide analytics platform can be used to identify ideal candidates for deep home energy upgrades, while a homeowner-facing dashboard presents homeowners with the economic rationale for pursuing a deep energy reduction strategy.

Multifamily Sector Capabilities

NREL and Radiant Labs are working to expand ResStock analysis capabilities to low-rise multifamily buildings. NREL will develop a database of multifamily housing stock characteristics, which will be used to automatically generate a set of statistically representative building energy models for the low-rise multifamily building sector.

These upgrades have excellent economics in almost every home to which they are applied. This suggests that the long payback period is not likely to be a barrier to market adoption. Other market barriers that apply regardless of the payback period include homeowner’s or contractor’s lack of knowledge, split incentives in rentals, and access to capital or financing.

learn more

U.S. Department of Energy. Quadrennial Energy Review Second Installment: Transforming the Nation’s Electricity System. Washington, D.C.: DOE, January 2017.

Contact DOE at technicalassistance@hq.doe.gov.

Wilson, E., et al. Electric End-Use Energy Efficiency Potential in the U.S. Single-Family Housing Stock, NREL/TP-5500-65667. NREL, 2016.

Utility or government incentives are a traditional way to address the long payback period barrier; these incentives are designed to bring payback periods down into an acceptable range for consumers. ResStock can identify cost-effective upgrades by home location, vintage, and heating fuel that would be prime candidates for incentives to reduce their otherwise long payback periods.

Further Exploration

This article covered some of the major results produced with ResStock to date. If you’re interested in digging deeper, you can explore the 48 state fact sheets, the interactive web visualizations, and the technical report described at the beginning of this article. You can also reach out to the authors to learn more about conducting your own analysis using the open-source ResStock capabilities. And check out “Producing Actionable Results with ResStock” to learn how NREL is partnering with other organizations to expand ResStock capabilities and to answer questions about energy and peak demand reductions in the residential building stock.

Erin Boyd, Ph.D., is a policy analyst for the Office of Climate, Environment, and Energy Efficiency at DOE. Eric Wilson is a research engineer at the National Renewable Energy Laboratory (NREL).

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